Staff Data Analyst

Responsibilities

• Work with leadership to proactively identify key company-level problems to solve, driving direct impact to top-line and bottom-line metrics.
• Drive strategic initiatives that span multiple domains and product lines, with measurable business impact.
• Take independent end-to-end ownership of broad data products and business questions, as well as questions at the data organization level.
• Demonstrate excellent judgement in prioritizing and executing both independently and through others.
• Navigate ambiguous questions and organizational challenges to land impact, managing upward, downward, and sideways across multiple stakeholders.
• Recommend clear actions and decisions for your business and product stakeholders to take, rather than presenting options without a point of view.
• Influence the roadmap and strategy of your domain, persuading stakeholders to act on the back of your analytical work.
• Fully manage stakeholder relationships: identify new stakeholders, build coalitions to influence business strategy, and leverage them to unblock execution.
• Communicate all aspects of your technical knowledge in a didactic and approachable way to all levels of the organization.
• Own the development and maintenance of key metrics with your stakeholders and data peers, setting data quality standards and defining metric layers.
• Ensure the data behind every analysis is accurate, reliable, and relevant, accounting for outliers, sparsity, sample size, imbalances, and missing or corrupted data, and cross-checking against independent internal sources where relevant.
• Clearly call out the methodological approaches considered, and document assumptions and caveats, statistical significance, and confidence intervals to prevent misinterpretation by stakeholders.
• Own the mentorship and professional development of junior and mid-level team members.

Requirements

• Bachelor’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, or similar), or equivalent practical experience.
• 5+ years in analytics, with a demonstrable track record of analyses that changed material business decisions.
• Expert-level SQL, including window functions and working with large-scale analytical databases.
• Strong proficiency in Python for analysis (pandas, NumPy, SciPy, scikit-learn, visualization libraries).
• Advanced experience with BI platforms and semantic modelling, with a focus on enabling self-serve analytics rather than producing dashboards on request.
• Excellent problem-solving skills and structured thinking applied to ambiguous or technically complex problems.
• Demonstrated ability to influence senior stakeholders without direct authority, build coalitions, and hold a position under pressure when the evidence supports it.
• Evidence of tech-leading or mentoring other analysts and raising the standard of a team, not only strong individual output.
• Excellent written and verbal communication, with the ability to make complex analysis legible to an executive audience.

Nice to have